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Hydrology and Earth System Sciences An interactive open-access journal of the European Geosciences Union
© Author(s) 2014. This work is distributed
under the Creative Commons Attribution 3.0 License.
Research article
06 Aug 2014
Review status
This discussion paper has been under review for the journal Hydrology and Earth System Sciences (HESS). The manuscript was not accepted for further review after discussion.
A coupled Bayesian and fault tree methodology to assess future groundwater conditions in light of climate change
J. J. Huang1, M. Du2, E. A. McBean3, H. Wang1, and J. Wang1 1State Key Laboratory of Simulation and Regulation of Water Cycle in River Basin, China Institute of Water Resources and Hydropower Research, Beijing, 100038, China
2Polytech Nice-Sophia, 930 Route des Colles, 06903 Sophia Antipolis, France
3School of Engineering, University of Guelph, Guelph, ON, N1G 2W1, Canada
Abstract. Maintaining acceptable groundwater levels, particularly in arid areas, while protecting ecosystems, are key measures against desertification. Due to complicated hydrological processes and their inherent uncertainties, investigations of groundwater recharge conditions are challenging, particularly in arid areas under climate changing conditions. To assist planning to protect against desertification, a fault tree methodology, in conjunction with fuzzy logic and Bayesian data mining, are applied to Minqin Oasis, a highly vulnerable regime in northern China. A set of risk factors is employed within the fault tree framework, with fuzzy logic translating qualitative risk data into probabilities. Bayesian data mining is used to quantify the contribution of each risk factor to the final aggregated risk. The implications of both historical and future climate trends are employed for temperature, precipitation and potential evapotranspiration (PET) to assess water table changes under various future scenarios. The findings indicate that water table levels will continue to drop at the rate of 0.6 m yr−1 in the future when climatic effects alone are considered, if agricultural and industrial production capacity remain at 2004 levels.

Citation: Huang, J. J., Du, M., McBean, E. A., Wang, H., and Wang, J.: A coupled Bayesian and fault tree methodology to assess future groundwater conditions in light of climate change, Hydrol. Earth Syst. Sci. Discuss., 11, 9361-9397, doi:10.5194/hessd-11-9361-2014, 2014.
J. J. Huang et al.
J. J. Huang et al.


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